{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/xsigra/Dropbox/Upload/Table7.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}11 Jul 2017, 12:16:31
{txt}
{com}. clear
{txt}
{com}. use "v-dem_coder2.dta"
{txt}(Written by R.              )

{com}. 
. *Model 1: EqProtec 
. clear
{txt}
{com}. use "v-dem_coder2.dta"
{txt}(Written by R.              )

{com}. gen phd=v2zzedlev>8 if v2zzedlev<.
{txt}(46,960 missing values generated)

{com}. gen gov=employ==2 if employ<.
{txt}(45,408 missing values generated)

{com}. keep country_id coder_id historical_date year v2clacjust_n v2clsocgrp_n v2clsnlpct_n phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred
{txt}
{com}. preserve
{txt}
{com}.  reshape long v2,i(country_id coder_id historical_date phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred) j(ind) string
{txt}(note: j = clacjust_n clsnlpct_n clsocgrp_n zzcurred zzfremrk zzgender zzreside zztimein)

Data{col 36}wide{col 43}->{col 48}long
{hline 77}
Number of obs.                 {res}  253379   {txt}->{res} 2.0e+06
{txt}Number of variables            {res}      14   {txt}->{res}      13
{txt}j variable (8 values)                     ->   {res}ind
{txt}xij variables:
{res}v2clacjust_n v2clsnlpct_n ... v2zztimein  {txt}->   {res}v2
{txt}{hline 77}

{com}.  encode ind,gen(indnumb)
{txt}
{com}.  drop if v2==.
{txt}(800,953 observations deleted)

{com}.  mixed v2  phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred || indnumb: || country_id:, robust  
{res}
{txt}Performing EM optimization: 
{res}
{txt}Performing gradient-based optimization: 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-22013.726}  
{res}{txt}Iteration 1:{space 3}log pseudolikelihood = {res:-22013.726}  
{res}
{txt}Computing standard errors:
{res}
{txt}Mixed-effects regression{col 49}Number of obs{col 67}={col 69}{res}   175,792

{txt}{hline 16}{c TT}{hline 44}
{col 17}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{hline 16}{c +}{hline 44}
{res}{col 9}indnumb{txt}{col 17}{c |}{res}{col 21}       3{col 31}   43,438{col 42} 58,597.3{col 53}   73,039
{col 6}country_id{txt}{col 17}{c |}{res}{col 21}     510{col 31}        1{col 42}    344.7{col 53}      999
{txt}{hline 16}{c BT}{hline 44}

{col 49}Wald chi2({res}2{txt}){col 67}={col 70}{res}        .
{txt}Log pseudolikelihood = {res}-22013.726{col 49}{txt}Prob > chi2{col 67}={col 73}{res}     .

{txt}{ralign 78:(Std. Err. adjusted for {res:3} clusters in indnumb)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}          v2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}phd {c |}{col 14}{res}{space 2}-.0114275{col 26}{space 2} .0176622{col 37}{space 1}   -0.65{col 46}{space 3}0.518{col 54}{space 4}-.0460448{col 67}{space 3} .0231898
{txt}{space 9}gov {c |}{col 14}{res}{space 2}-.0074041{col 26}{space 2}  .014147{col 37}{space 1}   -0.52{col 46}{space 3}0.601{col 54}{space 4}-.0351318{col 67}{space 3} .0203236
{txt}{space 2}v2zzgender {c |}{col 14}{res}{space 2} .0022518{col 26}{space 2} .0078154{col 37}{space 1}    0.29{col 46}{space 3}0.773{col 54}{space 4}-.0130661{col 67}{space 3} .0175698
{txt}{space 2}v2zzfremrk {c |}{col 14}{res}{space 2} .0087988{col 26}{space 2} .0047486{col 37}{space 1}    1.85{col 46}{space 3}0.064{col 54}{space 4}-.0005082{col 67}{space 3} .0181058
{txt}{space 2}v2zzreside {c |}{col 14}{res}{space 2}-.0001918{col 26}{space 2} .0000359{col 37}{space 1}   -5.34{col 46}{space 3}0.000{col 54}{space 4}-.0002622{col 67}{space 3}-.0001213
{txt}{space 2}v2zztimein {c |}{col 14}{res}{space 2} .0012825{col 26}{space 2} .0004706{col 37}{space 1}    2.73{col 46}{space 3}0.006{col 54}{space 4} .0003602{col 67}{space 3} .0022049
{txt}{space 2}v2zzcurred {c |}{col 14}{res}{space 2}  .002392{col 26}{space 2} .0029415{col 37}{space 1}    0.81{col 46}{space 3}0.416{col 54}{space 4}-.0033732{col 67}{space 3} .0081573
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4488669{col 26}{space 2} .0269844{col 37}{space 1}   16.63{col 46}{space 3}0.000{col 54}{space 4} .3959784{col 67}{space 3} .5017553
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 29}{c TT}{hline 48}
{col 30}{c |}{col 34}{col 46}Robust{col 63}
{col 3}Random-effects Parameters{col 30}{c |}{col 34}Estimate{col 45}Std. Err.{col 59}[95% Conf. Interval]
{hline 29}{c +}{hline 48}
{res}indnumb{txt}: Identity{col 30}{c |}
{col 19}var(_cons){col 30}{c |}{res}{col 33} .0015099{col 44} .0009017{col 58} .0004684{col 70} .0048669
{txt}{hline 29}{c +}{hline 48}
{res}country_id{txt}: Identity{col 30}{c |}
{col 19}var(_cons){col 30}{c |}{res}{col 33} .0437486{col 44}  .002282{col 58} .0394969{col 70} .0484579
{txt}{hline 29}{c +}{hline 48}
{col 16}var(Residual){col 30}{c |}{res}{col 33} .0741134{col 44} .0106198{col 58} .0559663{col 70} .0981447
{txt}{hline 29}{c BT}{hline 48}

{com}. restore
{txt}
{com}. 
. *Model 2: EqDist
. clear
{txt}
{com}. use "v-dem_coder2.dta"
{txt}(Written by R.              )

{com}. gen phd=v2zzedlev>8 if v2zzedlev<.
{txt}(46,960 missing values generated)

{com}. gen gov=employ==2 if employ<.
{txt}(45,408 missing values generated)

{com}. keep country_id coder_id historical_date year v2dlencmps_n v2dlunivl_n v2peedueq_n v2pehealth_n  phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred
{txt}
{com}. preserve
{txt}
{com}.  reshape long v2,i(country_id coder_id historical_date phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred) j(ind) string
{txt}(note: j = dlencmps_n dlunivl_n peedueq_n pehealth_n zzcurred zzfremrk zzgender zzreside zztimein)

Data{col 36}wide{col 43}->{col 48}long
{hline 77}
Number of obs.                 {res}  253379   {txt}->{res} 2.3e+06
{txt}Number of variables            {res}      15   {txt}->{res}      13
{txt}j variable (9 values)                     ->   {res}ind
{txt}xij variables:
{res}v2dlencmps_n v2dlunivl_n ... v2zztimein   {txt}->   {res}v2
{txt}{hline 77}

{com}.  encode ind,gen(indnumb)
{txt}
{com}.  drop if v2==.
{txt}(931,733 observations deleted)

{com}.  mixed v2  phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred || indnumb: || country_id:, robust 
{res}
{txt}Performing EM optimization: 
{res}
{txt}Performing gradient-based optimization: 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-58665.862}  
{res}{txt}Iteration 1:{space 3}log pseudolikelihood = {res:-58665.862}  
{res}
{txt}Computing standard errors:
{res}
{txt}Mixed-effects regression{col 49}Number of obs{col 67}={col 69}{res}   287,098

{txt}{hline 16}{c TT}{hline 44}
{col 17}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{hline 16}{c +}{hline 44}
{res}{col 9}indnumb{txt}{col 17}{c |}{res}{col 21}       4{col 31}   71,088{col 42} 71,774.5{col 53}   72,598
{col 6}country_id{txt}{col 17}{c |}{res}{col 21}     696{col 31}       10{col 42}    412.5{col 53}      906
{txt}{hline 16}{c BT}{hline 44}

{col 49}Wald chi2({res}3{txt}){col 67}={col 70}{res}        .
{txt}Log pseudolikelihood = {res}-58665.862{col 49}{txt}Prob > chi2{col 67}={col 73}{res}     .

{txt}{ralign 78:(Std. Err. adjusted for {res:4} clusters in indnumb)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}          v2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}phd {c |}{col 14}{res}{space 2} .0056475{col 26}{space 2} .0062305{col 37}{space 1}    0.91{col 46}{space 3}0.365{col 54}{space 4} -.006564{col 67}{space 3}  .017859
{txt}{space 9}gov {c |}{col 14}{res}{space 2}-.0596914{col 26}{space 2} .0250402{col 37}{space 1}   -2.38{col 46}{space 3}0.017{col 54}{space 4}-.1087694{col 67}{space 3}-.0106135
{txt}{space 2}v2zzgender {c |}{col 14}{res}{space 2}-.0255333{col 26}{space 2} .0101764{col 37}{space 1}   -2.51{col 46}{space 3}0.012{col 54}{space 4}-.0454787{col 67}{space 3}-.0055879
{txt}{space 2}v2zzfremrk {c |}{col 14}{res}{space 2} .0096859{col 26}{space 2} .0034375{col 37}{space 1}    2.82{col 46}{space 3}0.005{col 54}{space 4} .0029485{col 67}{space 3} .0164233
{txt}{space 2}v2zzreside {c |}{col 14}{res}{space 2}-.0002824{col 26}{space 2}  .000094{col 37}{space 1}   -3.00{col 46}{space 3}0.003{col 54}{space 4}-.0004666{col 67}{space 3}-.0000981
{txt}{space 2}v2zztimein {c |}{col 14}{res}{space 2} .0003119{col 26}{space 2} .0001978{col 37}{space 1}    1.58{col 46}{space 3}0.115{col 54}{space 4}-.0000758{col 67}{space 3} .0006997
{txt}{space 2}v2zzcurred {c |}{col 14}{res}{space 2} .0327923{col 26}{space 2} .0128583{col 37}{space 1}    2.55{col 46}{space 3}0.011{col 54}{space 4} .0075904{col 67}{space 3} .0579941
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4496923{col 26}{space 2} .0406355{col 37}{space 1}   11.07{col 46}{space 3}0.000{col 54}{space 4} .3700483{col 67}{space 3} .5293364
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 29}{c TT}{hline 48}
{col 30}{c |}{col 34}{col 46}Robust{col 63}
{col 3}Random-effects Parameters{col 30}{c |}{col 34}Estimate{col 45}Std. Err.{col 59}[95% Conf. Interval]
{hline 29}{c +}{hline 48}
{res}indnumb{txt}: Identity{col 30}{c |}
{col 19}var(_cons){col 30}{c |}{res}{col 33} .0004887{col 44} .0002591{col 58} .0001729{col 70} .0013813
{txt}{hline 29}{c +}{hline 48}
{res}country_id{txt}: Identity{col 30}{c |}
{col 19}var(_cons){col 30}{c |}{res}{col 33} .0468309{col 44} .0075781{col 58} .0341029{col 70} .0643092
{txt}{hline 29}{c +}{hline 48}
{col 16}var(Residual){col 30}{c |}{res}{col 33} .0869894{col 44} .0084529{col 58} .0719041{col 70} .1052397
{txt}{hline 29}{c BT}{hline 48}

{com}. restore
{txt}
{com}. 
. *Model 3: EqAcc
. clear
{txt}
{com}. use "v-dem_coder2.dta"
{txt}(Written by R.              )

{com}. gen phd=v2zzedlev>8 if v2zzedlev<.
{txt}(46,960 missing values generated)

{com}. gen gov=employ==2 if employ<.
{txt}(45,408 missing values generated)

{com}. keep country_id coder_id historical_date year v2pepwrses_n v2pepwrsoc_n v2pepwrgen_n phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred
{txt}
{com}. preserve
{txt}
{com}.  reshape long v2,i(country_id coder_id historical_date phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred) j(ind) string
{txt}(note: j = pepwrgen_n pepwrses_n pepwrsoc_n zzcurred zzfremrk zzgender zzreside zztimein)

Data{col 36}wide{col 43}->{col 48}long
{hline 77}
Number of obs.                 {res}  253379   {txt}->{res} 2.0e+06
{txt}Number of variables            {res}      14   {txt}->{res}      13
{txt}j variable (8 values)                     ->   {res}ind
{txt}xij variables:
{res}v2pepwrgen_n v2pepwrses_n ... v2zztimein  {txt}->   {res}v2
{txt}{hline 77}

{com}.  encode ind,gen(indnumb)
{txt}
{com}.  drop if v2==.
{txt}(760,165 observations deleted)

{com}.  mixed v2  phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred || indnumb: || country_id:, robust 
{res}
{txt}Performing EM optimization: 
{res}
{txt}Performing gradient-based optimization: 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-23139.434}  
{res}{txt}Iteration 1:{space 3}log pseudolikelihood = {res:-23139.434}  
{res}
{txt}Computing standard errors:
{res}
{txt}Mixed-effects regression{col 49}Number of obs{col 67}={col 69}{res}   217,443

{txt}{hline 16}{c TT}{hline 44}
{col 17}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{hline 16}{c +}{hline 44}
{res}{col 9}indnumb{txt}{col 17}{c |}{res}{col 21}       3{col 31}   72,103{col 42} 72,481.0{col 53}   72,934
{col 6}country_id{txt}{col 17}{c |}{res}{col 21}     522{col 31}       14{col 42}    416.6{col 53}      827
{txt}{hline 16}{c BT}{hline 44}

{col 49}Wald chi2({res}2{txt}){col 67}={col 70}{res}        .
{txt}Log pseudolikelihood = {res}-23139.434{col 49}{txt}Prob > chi2{col 67}={col 73}{res}     .

{txt}{ralign 78:(Std. Err. adjusted for {res:3} clusters in indnumb)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}          v2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}phd {c |}{col 14}{res}{space 2}-.0034383{col 26}{space 2} .0064168{col 37}{space 1}   -0.54{col 46}{space 3}0.592{col 54}{space 4} -.016015{col 67}{space 3} .0091385
{txt}{space 9}gov {c |}{col 14}{res}{space 2}-.0667822{col 26}{space 2} .0104595{col 37}{space 1}   -6.38{col 46}{space 3}0.000{col 54}{space 4}-.0872825{col 67}{space 3}-.0462819
{txt}{space 2}v2zzgender {c |}{col 14}{res}{space 2} -.002577{col 26}{space 2} .0058144{col 37}{space 1}   -0.44{col 46}{space 3}0.658{col 54}{space 4}-.0139731{col 67}{space 3}  .008819
{txt}{space 2}v2zzfremrk {c |}{col 14}{res}{space 2} .0149451{col 26}{space 2} .0029198{col 37}{space 1}    5.12{col 46}{space 3}0.000{col 54}{space 4} .0092224{col 67}{space 3} .0206678
{txt}{space 2}v2zzreside {c |}{col 14}{res}{space 2}-.0000277{col 26}{space 2} .0001057{col 37}{space 1}   -0.26{col 46}{space 3}0.793{col 54}{space 4}-.0002348{col 67}{space 3} .0001795
{txt}{space 2}v2zztimein {c |}{col 14}{res}{space 2} .0007444{col 26}{space 2} .0003644{col 37}{space 1}    2.04{col 46}{space 3}0.041{col 54}{space 4} .0000303{col 67}{space 3} .0014585
{txt}{space 2}v2zzcurred {c |}{col 14}{res}{space 2} .0127432{col 26}{space 2} .0042298{col 37}{space 1}    3.01{col 46}{space 3}0.003{col 54}{space 4} .0044529{col 67}{space 3} .0210335
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3263801{col 26}{space 2} .0291396{col 37}{space 1}   11.20{col 46}{space 3}0.000{col 54}{space 4} .2692676{col 67}{space 3} .3834926
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 29}{c TT}{hline 48}
{col 30}{c |}{col 34}{col 46}Robust{col 63}
{col 3}Random-effects Parameters{col 30}{c |}{col 34}Estimate{col 45}Std. Err.{col 59}[95% Conf. Interval]
{hline 29}{c +}{hline 48}
{res}indnumb{txt}: Identity{col 30}{c |}
{col 19}var(_cons){col 30}{c |}{res}{col 33} .0030934{col 44} .0016722{col 58} .0010722{col 70} .0089244
{txt}{hline 29}{c +}{hline 48}
{res}country_id{txt}: Identity{col 30}{c |}
{col 19}var(_cons){col 30}{c |}{res}{col 33} .0317691{col 44} .0072399{col 58} .0203247{col 70} .0496576
{txt}{hline 29}{c +}{hline 48}
{col 16}var(Residual){col 30}{c |}{res}{col 33} .0715562{col 44} .0052927{col 58} .0618996{col 70} .0827193
{txt}{hline 29}{c BT}{hline 48}

{com}. restore
{txt}
{com}. 
. *Model 4: Egal
.  
. clear
{txt}
{com}. use "v-dem_coder2.dta"
{txt}(Written by R.              )

{com}. gen phd=v2zzedlev>8 if v2zzedlev<.
{txt}(46,960 missing values generated)

{com}. gen gov=employ==2 if employ<.
{txt}(45,408 missing values generated)

{com}. keep country_id coder_id historical_date year phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred v2clacjust_n v2clsocgrp_n v2clsnlpct_n v2dlencmps_n v2dlunivl_n v2peedueq_n v2pehealth_n v2pepwrses_n v2pepwrsoc_n v2pepwrgen_n 
{txt}
{com}. preserve
{txt}
{com}.  reshape long v2,i(country_id coder_id historical_date phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred) j(ind) string
{txt}(note: j = clacjust_n clsnlpct_n clsocgrp_n dlencmps_n dlunivl_n peedueq_n pehealth_n pepwrgen_n pepwrses_n pepwrsoc_n zzcurred zzfremrk zzgender zzreside zztimein)

Data{col 36}wide{col 43}->{col 48}long
{hline 77}
Number of obs.                 {res}  253379   {txt}->{res} 3.8e+06
{txt}Number of variables            {res}      21   {txt}->{res}      13
{txt}j variable (15 values)                    ->   {res}ind
{txt}xij variables:
{res}v2clacjust_n v2clsnlpct_n ... v2zztimein  {txt}->   {res}v2
{txt}{hline 77}

{com}.  encode ind,gen(indnumb)
{txt}
{com}.  drop if v2==.
{txt}(1,994,081 observations deleted)

{com}.  mixed v2  phd gov v2zzgender v2zzfremrk v2zzreside v2zztimein v2zzcurred || indnumb: || country_id:, robust  /* THIS TOOK THREE HOURS TO RUN! */
{res}
{txt}Performing EM optimization: 
{res}
{txt}Performing gradient-based optimization: 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-105789.55}  
{res}{txt}Iteration 1:{space 3}log pseudolikelihood = {res:-105789.55}  
{res}
{txt}Computing standard errors:
{res}
{txt}Mixed-effects regression{col 49}Number of obs{col 67}={col 69}{res}   680,333

{txt}{hline 16}{c TT}{hline 44}
{col 17}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{hline 16}{c +}{hline 44}
{res}{col 9}indnumb{txt}{col 17}{c |}{res}{col 21}      10{col 31}   43,438{col 42} 68,033.3{col 53}   73,039
{col 6}country_id{txt}{col 17}{c |}{res}{col 21}   1,728{col 31}        1{col 42}    393.7{col 53}      999
{txt}{hline 16}{c BT}{hline 44}

{col 49}Wald chi2({res}7{txt}){col 67}={col 70}{res}   286.62
{txt}Log pseudolikelihood = {res}-105789.55{col 49}{txt}Prob > chi2{col 67}={col 73}{res}0.0000

{txt}{ralign 78:(Std. Err. adjusted for {res:10} clusters in indnumb)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}          v2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}phd {c |}{col 14}{res}{space 2}-.0015599{col 26}{space 2} .0057082{col 37}{space 1}   -0.27{col 46}{space 3}0.785{col 54}{space 4}-.0127476{col 67}{space 3} .0096279
{txt}{space 9}gov {c |}{col 14}{res}{space 2}-.0502098{col 26}{space 2} .0128505{col 37}{space 1}   -3.91{col 46}{space 3}0.000{col 54}{space 4}-.0753963{col 67}{space 3}-.0250234
{txt}{space 2}v2zzgender {c |}{col 14}{res}{space 2}-.0112363{col 26}{space 2} .0059152{col 37}{space 1}   -1.90{col 46}{space 3}0.057{col 54}{space 4}-.0228298{col 67}{space 3} .0003572
{txt}{space 2}v2zzfremrk {c |}{col 14}{res}{space 2} .0109259{col 26}{space 2} .0020263{col 37}{space 1}    5.39{col 46}{space 3}0.000{col 54}{space 4} .0069544{col 67}{space 3} .0148975
{txt}{space 2}v2zzreside {c |}{col 14}{res}{space 2}-.0001773{col 26}{space 2} .0000597{col 37}{space 1}   -2.97{col 46}{space 3}0.003{col 54}{space 4}-.0002943{col 67}{space 3}-.0000602
{txt}{space 2}v2zztimein {c |}{col 14}{res}{space 2}   .00069{col 26}{space 2} .0002164{col 37}{space 1}    3.19{col 46}{space 3}0.001{col 54}{space 4} .0002658{col 67}{space 3} .0011142
{txt}{space 2}v2zzcurred {c |}{col 14}{res}{space 2} .0184785{col 26}{space 2} .0067177{col 37}{space 1}    2.75{col 46}{space 3}0.006{col 54}{space 4} .0053121{col 67}{space 3} .0316449
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4134508{col 26}{space 2} .0265275{col 37}{space 1}   15.59{col 46}{space 3}0.000{col 54}{space 4} .3614578{col 67}{space 3} .4654437
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 29}{c TT}{hline 48}
{col 30}{c |}{col 34}{col 46}Robust{col 63}
{col 3}Random-effects Parameters{col 30}{c |}{col 34}Estimate{col 45}Std. Err.{col 59}[95% Conf. Interval]
{hline 29}{c +}{hline 48}
{res}indnumb{txt}: Identity{col 30}{c |}
{col 19}var(_cons){col 30}{c |}{res}{col 33} .0031287{col 44} .0018931{col 58} .0009557{col 70} .0102427
{txt}{hline 29}{c +}{hline 48}
{res}country_id{txt}: Identity{col 30}{c |}
{col 19}var(_cons){col 30}{c |}{res}{col 33} .0412725{col 44} .0040792{col 58} .0340041{col 70} .0500945
{txt}{hline 29}{c +}{hline 48}
{col 16}var(Residual){col 30}{c |}{res}{col 33} .0788658{col 44} .0048632{col 58} .0698875{col 70} .0889974
{txt}{hline 29}{c BT}{hline 48}

{com}. restore
{txt}
{com}. 
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  {txt}log type:  {res}smcl
 {txt}closed on:  {res}11 Jul 2017, 12:35:26
{txt}{.-}
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